Conference Publication Details
Mandatory Fields
Shortt A.;Naughton T.;Javidi B.
Proceedings of SPIE - The International Society for Optical Engineering
Nonuniform quantization compression of digital holograms of three-dimensional objects using artificial neural networks
Optional Fields
Artificial neural networks Digital holography Image compression Kohonen competitive neural network Kohonen self-organizing map Kohonen vector quantization network Three-dimensional image processing
We propose two lossy data compression techniques for complex-valued digital holograms of three-dimensional objects. The techniques employ unsupervised artificial neural networks to nonuniformly quantize the real and imaginary values of digital holograms. The digital holograms of real-world three-dimensional objects were captured using phase-shift interferometry. Our techniques are compared experimentally with the uniform quantization approach, and with an alternative nonuniform quantization technique based on the k-means clustering algorithm.
Grant Details